chrysopoetics

Parkinson Historical Volatility

First off, a huge thank you to the following people:

theheirophant: www.tradingview.com/u/theheirophant/
alexgrover: www.tradingview.com/u/alexgrover/
NGBaltic: www.tradingview.com/u/NGBaltic/

The Parkinson Historical Volatility (PHV), developed in 1980 by the physicist Michael Parkinson, aims to estimate the volatility of returns for a random walk using the high and low in any particular period. An important use of the PHV is the assessment of the distribution prices during the day as well as a better understanding of the market dynamics. Comparing the PHV and a periodically sampled volatility helps traders understand the tendency towards mean reversion in the market as well as the distribution of stop-losses.

This script allows you to transform the volatility reading. The intention of this is to be able to compare volatility across different assets and timeframes. Having a relative reading of volatility also allows you to better gauge volatility within the context of current market conditions.

For the signal lie I chose a repulsion moving average to remove choppy crossovers of the estimator and the signal. This may have been a mistake, so in the near-future I might update so that the MA can be selected. Let me know if you have any opinions either way.

References
www.rdocumentation.o...-4/topics/volatility
www.ivolatility.com/help/3.html

Want to Learn?

If you'd like the opportunity to learn Pine but you have difficulty finding resources to guide you, take a look at this rudimentary list: docs.google.com...k0VGHViQc4/edit?usp=sharin...

The list will be updated in the future as more people share the resources that have helped, or continue to help, them. Follow me on Twitter to keep up-to-date with the growing list of resources.

Suggestions or Questions?

Don't even kinda hesitate to forward them to me. My (metaphorical) door is always open.

Skrypt open-source

Zgodnie z prawdziwym duchem TradingView, autor tego skryptu opublikował go jako open-source, aby traderzy mogli go zrozumieć i zweryfikować. Brawo dla autora! Możesz używać go za darmo, ale ponowne wykorzystanie tego kodu w publikacji jest regulowane przez Dobre Praktyki. Możesz go oznaczyć jako ulubione, aby użyć go na wykresie.

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